The high strength and hard-to-cut materials can be easily machined by using modern machining methods. It is important to introduce the efforts on enhancing the process for improving the machining ...quality. In the present investigation, an effort was made to analyze the effects of micro-size Al2O3 particles mixed into Kerosene as the dielectric under different powder concentrations on machining titanium alloy in Electrical Discharge Machining (EDM). Response Surface Methodology (RSM) based algorithm utilized to analyze the performance measures by considering machining time with Cost of Goods Manufactured (COGM) method in Powder Mixed Electro Discharge Machining (PMEDM) process. It was found that the micron size powders can significantly help to enhance the surface quality of the Ti-6Al-4V during machining in the PMEDM process. The presence of carbon, oxygen elements and the formation of surface oxides and carbides has been found due to the decomposition of dielectric fluid in the PMEDM process. The lower deep cavities and uniform of PMEDM’s surface have been produced by added Al2O3 powder into the EDM process owing to lower surface cracks density, conductivity.
Background:
Healthcare workers are frontline responders facing a disproportionate increase in occupational responsibilities during the COVID-19 pandemic. Added work-related stress among healthcare ...personnel may lead to personal and work-related repercussions, such as burnout or decreased quality of care for patients; however, little is known about how the COVID-19 pandemic affects the daily work and life of these workers. This study aimed to evaluate the personal and occupational impacts of the COVID-19 induced partial lockdown in Vietnam among hospital staff.
Methods:
A cross-sectional web-based study was carried out to collect demographic data and the personal and job impacts of respondents during the second week of national lockdown in April 2020. Snowball sampling technique was applied to recruit 742 hospital staff. The exploratory factor analysis (EFA) was used to examine the validity of the instrument.
Results:
Of the 742 respondents, 21.2% agreed that “working attitude well-maintained,” followed by 16.1% of respondents who reported that there were “enough employees at work.” Only 3.2% of respondents agreed that “their work was appreciated by society.” Furthermore, healthcare workers in the central region were less likely to have experienced “Avoidance of disclosure and discrimination related to COVID-19” than other areas (Coef. = – 0.25, CI: −0.42 to −0.07). Being women also had a negative association with scores in “Avoidance of disclosure and discrimination related to COVID 19” domain (Coef. = −0.27, CI: −0.43 to −0.12) while having a positive association with “negative attitude towards working conditions” domain (Coef. = 0.19, CI: 0.09 to 0.3). In addition, working in administrative offices (Coef. = 0.20; 95% CI = 0.05 to 0.36) and infectious departments (Coef. = 0.36; 95% CI = 0.09 to 0.63) had a positive association with “Increased work pressure due to COVID 19” domain.
Conclusion:
These findings revealed marginal impacts of the COVID-19 pandemic on the work and life of hospital staff in Vietnam. Furthermore, this study highlighted the importance of implementing preventive strategies during the nationwide partial lockdown to manage hospital admissions and the burden on healthcare workers. Finally, this study characterizes targeted demographics that may benefit from appreciation by employers and society during a national pandemic.
Abstract
Purpose
Recoil length minimization is always been a top concern in various structural, industrial, and defence applications. The traditional passive recoil system is not able to respond ...quickly to the changes in the impact force. These limitations can be overcome by introducing a semi-active recoil system, which comprises an intelligent fluid damper.
Design, methodology, and approach
The electrorheological (ER) fluid, which responds to the applied electric field and exhibits high yield strength, will be a proper damper for the recoil system. An ER damper can bring back the vibrating system to its equilibrium in a brief period. In this article, the general design procedure of an ER fluid semi-active damper has been developed, which is suitable for a recoil system. The equations of damping forces (viscous, quadratic, and ER) are modified in terms of geometric parameter, namely the piston diameter (
D
P
), which can be selected to obtain the desired dynamic range (greater than two) and optimum damping force. With the MATLAB software, the damper and spring specifications are fixed to meet the required conditions, viz. the dynamic range should be greater than two, and the total damping and spring force should counter-recoil the system.
Findings
Results obtained for a case study of gunfire conclude that the recoil system developed using design specifications exhibits desired performance with maximum recoil of 75.59 mm at 80°, angle of elevation, which is within the allowable range of 150 mm. It is shown that the rate of firing can be increased by decreasing the recoil length.
Originality and value
The novel procedure for the design of ER damper outlined in this work will be helpful for any recoil length minimization problem.
In electrical discharge machining (EDM), the productivity and machined surface quality is directly influenced by the properties of the electrode surface material layer used. In the present study, a ...research attempt was made to find the optimal technological parameters in EDM process with AlCrNi coated electrode using Taguchi-Data Envelopment Analysis based Ranking (DEAR) based multi-response optimization approach. From the experimental investigation, the optimal technological parameter combination in EDM using AlCrNi coated electrode was found as peak current (40 A), voltage (55 V), and pulse-on-time (1000 μs) on machining Ti-6Al-4V titanium alloy. The current was found as more principal factor in EDM process with coated tool due to the electrical conductance of the tool coating. The better surface topography with lower surface roughness and micro cracks can be obtained on the machined specimens with proposed parameter combination.
Although the pathogenesis of depressive disorders is not fully elucidated, untreated adolescent depression can lead to serious sequelae such as impaired academic performance and social functioning, ...substance use disorders, poor self-esteem, and increased risk for suicidal ideation and attempts. Literature on adolescent mental health in Vietnam is limited, despite increased international awareness of this critical issue. This study aimed to investigate the prevalence and associations of depressive symptoms in Vietnamese adolescents.
A cross-sectional, self-administered survey was conducted in five provinces of Vietnam among adolescents aged 14 to 24 years. In addition to collecting participants' demographics, a structured questionnaire was developed to examine depressive symptoms, suicidal ideation, loneliness, and cyberbullying victimization. Depressive symptoms and loneliness were assessed
the PHQ-9 and UCLA Loneliness Scale, respectively. Two-tailed Chi-squared, Mann-Whitney, and Kruskal-Wallis tests were performed to examine associations between variables. Multivariate Logistic regression models were conducted to examine the associations between prior-defined variables and positive depressive symptoms.
Among 1,600 respondents, 31.8% of participants reported having mild-moderate or severe depressive symptoms. Participants within the moderate-severe depressive symptom group had significantly lower community cohesion scores than those of participants in normal and mild depressive symptom groups (
< 0.05). Youths living alone were more likely to have moderate-severe depressive symptoms (OR 2.16; 95% CI: 1.09-4.25). Cyberbullying had significant associations with depressive severity (OR 1.93; 95% CI 1.38-2.70).
The findings of this study characterize various risk and protective factors for depression in Vietnamese youths and adolescents. The results highlight the importance of raising awareness and increasing access to educational resources for depression and other mental health illnesses. With the rising prevalence of depression, parents, teachers, and community leaders play a vital role in addressing mental health problems in adolescents.
In the field of in-process monitoring for the production of safety-critical parts, the utilization of Machine Learning (ML) models has demonstrated promising potential for enhancing the manufacturing ...process. Specifically, Supervised Classification Algorithms, selected based on the complexity of the problem, can significantly improve the performance of ML models. While ML primarily relies on training data to comprehend input-output relationships, its ability to draw rapid conclusions is noteworthy. Deep neural networks have emerged as valuable tools, offering more accurate analytical data compared to Finite Element Method (FEM) models. They present a cost-effective alternative to empirical data by incorporating error compensation in a closed loop. Nevertheless, vision-based techniques, such as those used in this study, necessitate high-quality input images and demand substantial computational power for image classification. To address these challenges, this study proposes the use of a shallow Convolutional Neural Network (CNN)-based architecture for detecting in-process defects in parts manufactured using Additive Manufacturing (AM) technology. Complementing this, Support Vector Machine (SVM) and Extreme Learning Machine (ELM) algorithms are integrated with the CNN architecture. Additionally, the research takes into account the high costs associated with data collection and installation, data unavailability, challenges in data labeling, as well as common difficulties like overfitting and underfitting of ML models. These factors often pose constraints on the application of ML solutions within the context of AM. The study aims to address these issues and shed light on the potential of ML for AM applications. By employing a combination of CNN, SVM, and ELM algorithms, this research delves into the effectiveness of ML models in defect detection during the AM process. The insights derived from this study contribute to mitigating the aforementioned limitations and pave the way for a broader adoption of ML solutions in AM. This optimization aims to enhance performance, reduce costs, and improve the overall quality of manufactured parts.
In the present scenario, great effort is expended to improve the machining process by adopting multi-criteria decision making in electrical discharge machining (EDM). In this research article, an ...attempt was made to optimize the process parameters of EDM with Nickel Coated Aluminium Electrode for machining Titanium Alloy using Preference Selection Index (PSI). The experimental work were performed using Taguchi based L16 orthogonal to solve multi-objective optimization problem. The current (
I
), voltage (
U
) and pulse on time (
T
on
) were used as input response variables for investigation process while material removal rate (MRR) and tool wear rate (TWR) were selected as performance measures. The experimental results show that set of optimized parameters of the multi-objective optimization problem in EDM with nickel coated aluminium electrode could improve the machining with better surface measures with less deviation from the prediction. The combination between PSI and Taguchi method reduced and saved significantly the experimental time and cost and increased accuracy for optimization process.
The titanium alloy specimens are generally utilized in many manufacturing applications due to their higher corrosion resistance and lower density. Since it is highly tedious to machine such materials ...using conventional machining processes, it can be easily machined using micro Electrical Discharge Machining (EDM). In the present study, an attempt was made to optimize the process parameters on machining titanium alloy specimens with tungsten carbide in micro EDM process. Taguchi-Topsis method was used to derive better process factors such as voltage, capacitance and Electrode rotational speed. Depth of machining, Overcut and tool wear were considered as quality measures to evaluate the machining characteristics. It was found that 160 V of voltage could produce better machinability with the capacitance of 10 nF and electrode speed of 400 rpm. It was also found that the parameters can produce a better surface finish with better machining accuracy. The only fewer agglomeration of tool electrodes was observed over the machined titanium specimen.
Falls are a significant health concern for older adults and people with disabilities. It can result in serious injuries such as hip fractures, head trauma, and even death. Therefore, a fall detection ...system is essential for preventing and mitigating the abovementioned negative consequences. In this study, we propose a fall detection system with a low-cost camera that can run in real-time and obtain persuading accuracy. Concretely, our proposed system first detects and tracks entities using the Yolo-V4-tiny model and SORT algorithm, respectively. Subsequently, the MediaPipe framework is utilized to extract the skeletons of each entity for physical characteristics calculations. Last but not least, the provided skeletons per frame with their corresponding physical characteristics serve as inputs of the Transformer to release detection results. The experimental result with reliable accuracy suggests that our study has the potential for practical applications. The demo video can be found here https://www.youtube.com/watch?v=dyFUT_SBrfU.
Modern automobile technology is pushing towards maximizing road safety, connected vehicles, autonomous vehicles, etc. Automotive RADAR is core sensor technology used for ADAS (Advanced Driver ...Assistance Technology), ACC (Adaptive Cruise Control), AEB (Automatic Emergency Braking System), traffic assistance, parking aid, and obstacle/pedestrian detection. Despite being inexpensive, RADAR technology provides robust results in harsh conditions such as harsh weather, extreme temperature, darkness, etc. However, the performance of these systems depends on the position of the RADAR and its characteristics like frequency, beamwidth, and bandwidths. Moreover, the characterization of varied materials like layers of paint, polish, primer, or layer of rainwater needs to be analyzed. This performance can be predicted through real-time simulation using advanced FEM software like Altair FEKO&WinProp. These simulations can provide valuable insight into the performance of the system, allowing engineers to optimize the system for specific use cases. For example, simulation can be used to determine the optimal parameters of the RADAR system for a given application. This information can then be used to design and build a physical model or prototype that is optimized for the desired performance. These simulations play a prominent role in determining appropriate data collection and sensor fusion, which reduces the cost and time required for the development of a physical model or prototype. The continued growth and demand for advanced safety features in vehicles further highlight the importance of RADAR technology in modern automobile technology. By accurately characterizing the environment and simulating the system's behavior in real time, engineers can optimize RADAR systems for specific use cases, contributing to safer and more efficient driving experiences
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